Big data and credit risk assessment: a bibliometric review, current streams, and directions for future research

被引：5

作者：

Nobanee, Haitham ^{[1
,2
,3
]}

Shanti, Hiba ^{[1
]}

Aldhanhani, Hind ^{[1
]}

Alblooshi, Abdulrahman ^{[1
]}

Alali, Essa ^{[1
]}

机构：

[1] Abu Dhabi Univ, Coll Business, Dept Accounting & Finance, Abu Dhabi, U Arab Emirates

[2] Univ Oxford, Oxford Ctr Islamic Studies, Oxford, England

[3] Univ Liverpool, Fac Humanities & Social Sci, Liverpool, Merseyside, England

来源：

COGENT ECONOMICS & FINANCE | 2022年 / 10卷 / 01期

关键词：

credit risk; network mapping; risk assessment; bibliometric; big data; BANKRUPTCY PREDICTION; ENSEMBLE; SCIENCE;

D O I：

10.1080/23322039.2022.2132638

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This study aims to track the structural development of academic research on credit risk assessment and big data using bibliometric analysis. The bibliography is obtained from the Scopus database and contains all studies with citations published between 2012 and 2021. The study's findings suggest that credit risk assessment and big data are vast fields that have increased significantly in the last nine years. Chinese researchers and organizations contributed the most to the documents. The current study concludes that several possibilities exist to improve the knowledge of credit risk assessment and big data.

引用

页数：18

共 61 条

[1] Credit Risk Analysis Using Machine and Deep Learning Models [J].